Short-term power forecasting system for photovoltaic plants

  1. Fernandez-Jimenez, L.A. 1
  2. Muñoz-Jimenez, A. 1
  3. Falces, A. 1
  4. Mendoza-Villena, M. 1
  5. Garcia-Garrido, E. 1
  6. Lara-Santillan, P.M. 1
  7. Zorzano-Alba, E. 1
  8. Zorzano-Santamaria, P.J. 1
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Journal:
Renewable Energy

ISSN: 0960-1481

Year of publication: 2012

Volume: 44

Issue: 8

Pages: 311-317

Type: Article

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DOI: 10.1016/J.RENENE.2012.01.108 SCOPUS: 2-s2.0-84858281861 WoS: WOS:000302821800036 GOOGLE SCHOLAR

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Abstract

This paper presents a new statistical short-term forecasting system for a grid-connected photovoltaic (PV) plant. The proposed system comprises three modules composed of two numerical weather prediction models and an artificial neural network based model. The first two modules are used to forecast weather variables used by the third module, which has been selected from a set of different models. The final forecast value is the hourly energy production in the PV plant. The forecasting horizon ranges from 1 to 39 h, covering all of the following day. The forecast values can be used for determining the most favourable hours to carry out maintenance tasks in the plant, and for preparing bid offers to the electricity market. © 2012 Elsevier Ltd.